Conference Agenda

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Ground remote sensing by GNSS has been a research topic for the Institute of Geodesy and Photogrammetry (IGP) for some years. In the context of the Hydrology & Cryosphere research of Dragon 4 programme we focus on the determination of the snow water equivalent and of the snow depth. Beside these experimental observations we have been carrying out measurements in order to better assess the propagation of GNSS signals in water. A further interesting, however, not yet really elaborated topic is the measurement of the soil moisture in the frame of landslide hazard monitoring.

In the case of snow water determination we devised a method where GNSS receivers buried in the snow cover are used. From differential measurements between 'snow-free' and 'snow-covered' receivers the water content can be inferred. However, to this end a special refractivity model has been developed and accounted for in the GNSS data treatment. For the determination of the snow height we are mesuring reflected signals in a geometric mode or as applied by different authors, we use the SNR data directly. The propagation through water has been investigated on a dedicated experiment, where we could show the extinction of the signal at roughly 3 cm penetration depth. The water depth can be determined by the geometric analysis of the GNSS signal. Permafrost ground might be a hazard especially if it is located on steep slopes. This is the case in the Alps where Rock Glacier are commonly encountered. The main hazard is due to warm up and to a partial de-freezing. This might be reflected in changing soil/ground moisture. Therefore, the information on this parameter could be one piece of the puzzle in natural hazard assement in alpine areas. We showed, that the temperature and the movements are highly correlated and might even allow for an inversion of the data to determine the sliding horizon.

Soil moisture, the amount of water contained in the soil, is an environmental descriptor that integrates much of the land surface hydrology. From agriculture production to flood and drought prediction, soil moisture plays an important role in human production and human life. Soil moisture monitoring based on GNSS-R technique has been proposed to measure soil moisture using GNSS signals reflected from land surface. It is economical, flexible and able to work all weather and all day. It is a good supplement to current soil moisture observation methods. GNSS signal reflection process over bare land and reflected signal characteristics are explained theoretically. Then retrieval theory is introduced briefly. It can be seen that satellite elevation and azimuth have direct relevance to key parameters involved in soil moisture monitoring, especially surface roughness and antenna gain, which adds complications to the practical application of this technique. Fortunately, BDS GEO satellites have fixed positions relative to earth surface, resulting in constant elevation and azimuth and thus a constant influnce of parameters above. Finally, soil moisture monitoring method using reflected signals of BDS GEO satellites is proposed and its signal processing flow is presented as well. A ground-based experiment was carried out to validate the retrieval method. A RHCP antenna was set up to sky to receive the direct signal while an LHCP antenna was set pointing to the field covered with wheat at initial growth stage. We collected the GPS L1 and BDS B1 signals using a multi-channel GNSS intermediate frequency signal sampler. And the true value of soil moisture was collected by oven drying method once per hour during the experiment period. Then data processing was conducted according to the signal processing flow. Experiment results show an agreement with the true values. Forther more, the results of BDS GEO satellites present a better performance in both accuracy and temporal continuity owing to the fixed position of GEO satellites. We introduce the soil moisture retrieval principle, propose a retrieval method using BDS GEO signals and present the experiment results dedicated to validate method performance. However, priori information of soil composition, surface roughness and antenna gain is needed to obtain a better performance. As result simplified and valid models needs to be further studied. Machine learning algorithms can be applied to this technique, for example.

Poster

Characteristics and Limitations of Submerged GPS L1 Observations

Ladina Steiner

ETH Zurich, Switzerland

Extensive amount of water stored in snow covers has a high impact on flood development during snow melting periods. Early assessment of these parameters in mountain environments enhance early-warning and thus prevention of major impacts. Sub-snow GNSS techniques are lately suggested to determine liquid water content, snow water equivalent or considered for avalanche rescue. GNSS antennas are submerged into soil to derive soil moisture. This technique is affordable, flexible, and provides accurate and continuous observations independent on weather conditions. However, the characteristics of GNSS observations for applications within a snow-pack or submerged into water still need to be further investigataed.

The magnitude of the main interaction processes involved for the GPS wavelength propagating through different layers of snow, ice or water is examined theoretically. Liquid water exerts the largest influence on GPS signal propagation through a snow-pack. Therefore, we focus on determining the characteristics of GNSS observables under water.

An experiment was set-up to investigate the characteristics and limitations of submerged GPS observations using a pool, a level control by communicating pipes, a geodetic and a low-cost GPS antenna, and a water level sensor. The GPS antennas were placed into the water. The water level was increased daily by a step of two millimeters up to thirty millimeters above the antenna. Based on this experiment, the signal penetration depth, satellite availability, the attenuation of signal strength and the quality of solutions are analysed. Our experimental results show an agreement with the theoretically derived attenuation parameter and signal penetration depth.

The assumption of water as the limiting parameter for GPS observations within a snow-pack can be confirmed. Higher wetness in a snow-pack leads to less transmission, higher refraction, higher attenuation and thus a decreased penetration depth as well as a reduced quality of the solutions.

In consequence, GPS applications within a snow-pack are heavily impacted by wetness which is even more pronounced during melting period.

Placing the antenna in a fresh water layer as for soil moisture retrievel, a high attenuation of signal strength leads to a signal penetration up to 3.5 centimeter.

In this poster, we present a short introduction to the principle, explain the developed algorithms and show results of experiments dedicated to the signal propagation in water.